Evidence map›Paper›PMID 31897310›Full record

ReviewSultan Qaboos University medical journal2019

The Value of Programmed Death Ligand 1 Expression in Cancer Patients Treated with Neoadjuvant Chemotherapy.

Malika Al-Dughaishi, Asem Shalaby, Khawla Al-Ribkhi, Ammar Boudaka, Mohamed-Rachid Boulassel, Jumana Saleh

Open access · diamondAbstract readReview
In one paragraph

Review in Sultan Qaboos University medical journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 40% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Malika Al-DughaishiDepartment of Biochemistry, Sultan Qaboos University, Muscat, Oman.
Asem ShalabyDepartment of Pathology, Sultan Qaboos University, Muscat, Oman.
Khawla Al-RibkhiDepartment of Biochemistry, Sultan Qaboos University, Muscat, Oman.
Ammar BoudakaDepartment of Physiology, Sultan Qaboos University, Muscat, Oman.
Mohamed-Rachid BoulasselDepartment of Biomedical Sciences, Sultan Qaboos University, Muscat, Oman.
Jumana SalehDepartment of Biochemistry, Sultan Qaboos University, Muscat, Oman.
Sultan Qaboos University · OM

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Programmed death ligand 1 (PD-L1) is an inhibitory molecule expressed by cancer cells to supress T-cell activity and escape anti-tumour immunity. The role of PD-L1 in cancer has been studied extensively as it is considered an important immune checkpoint against immune over-activation through its interaction with Programmed death receptor 1 (PD-1) expressed on activated lymphocytes. PD-L1 expression was found to be enhanced by chemotherapy through different proliferation pathways. However, the predictive and prognostic value for PD-L1 expression in cancer patients treated with neoadjuvant chemotherapy (NAC) is not yet established. This review focused on the potential effects of chemotherapy on PD-L1 expression and the role of PD-L1 as a prognostic and predictive marker in NAC-treated cancer patients. In addition, the potential use of this marker in clinical practice is discussed.

Indexed as

Neoadjuvant TherapyAntineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorHumansLymphocytes, Tumor-InfiltratingNeoplasmsProgrammed Cell Death 1 ReceptorTreatment OutcomeBiomarkers, TumorProgrammed Cell Death 1 ReceptorCancerNeoadjuvant TherapyProgrammed Cell Death 1 Ligand 1Programmed Cell Death 1 Receptor

Identifiers

PMID31897310
PMCPMC6930029
OpenAlexW2998767211

What OpenQuestion holds

Textmetadata
LicenceCC BY-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.